The compression of videos using variable-bit-rate encoding produces constant quality video at the expense of significant bit-rate variability. Intelligent traffic smoothing techniques are needed to support efficient network resource utilization. In this paper, we examine a class of bandwidth smoothing algorithms and propose a novel enhancement that uses dynamic programming (DP) to improve upon ...

Dynamic Programming (DP) algorithm has been studied from 1940s and successfully applied to pattern recognition fields such as continuous speech recognition, hand writing recognition, gesture recognition and so on. In this paper, we propose a novel hand gesture recognition system which includes three kinds of image processing: skin area segmentation, motion estimation by a retina-V1 model, and a...

Dynamic Programming (DP) is one of the most classical methods adopted for reservoir operation. It reduces computational efforts complex high-dimensional problems by piecewise dimensionality reduction and provides global optimums problems, but it suffers “curse dimensionality”. Progressive Optimality Algorithm (POA) has been used repeatedly in operation studies during last decades because allevi...

We present a new method to compute upper bounds of the number of solutions of binary integer programming (BIP) problems. Given a BIP, we create a dynamic programming (DP) table for a redundant knapsack constraint which is obtained by surrogate relaxation. We then consider a Lagrangian relaxation of the original problem to obtain an initial weight bound on the knapsack. This bound is then refine...

This paper presents a method for extracting building roof contours from digital images collected over urban landscapes. The proposed method utilizes an energy function based on snakes that represents building roof contours in digital images and is optimized with a dynamic programming (DP) algorithm. Because most building roof contours are characterized by rectilinear sides that intercept at rig...

We consider an integer stochastic knapsack problem (SKP) where the weight of each item is deterministic, but the vector of returns for the items is random with known distribution. The objective is to maximize the probability that a total return threshold is met or exceeded. We study several solution approaches. Exact procedures, based on dynamic programming (DP) and integer programming (IP), ar...

Given a set of n items with profits and weights and a knapsack capacity C, we study the problem of finding a maximal knapsack packing that minimizes the profit of selected items. We propose for the first time an effective dynamic programming (DP) algorithm which has O(nC) time complexity and O(n+C) space complexity. We demonstrate the equivalence between this problem and the problem of finding ...

The detection and tracking of small targets under low signal-to-clutter ratio (SCR) has been a challenging task for infrared search track (IRST) systems. Track-before-detect (TBD) is widely-known algorithm which can solve this problem. However, huge computation costs storage requirements limit its application. To address these issues, dynamic programming (DP) multiple hypothesis testing (MHT)-b...

one major branch in mathematical sciences, which recently has been given especial attention, is optimization, including various methods such as linear programming, integer programming, and dynamic programming. due to the unique characteristics of air treatment systems, specifically multistage nature of such systems, dynamic programming has been widely applied. the purpose of this paper is to fi...

The lithography used for 32 nanometers and smaller VLSI process technologies restricts the admissible interconnect widths and spaces to very few discrete values with some interdependencies, making traditional interconnect sizing by continuous-variable optimization techniques impossible. Single-net bottom-up power-delay optimization for discrete wire widths has been solved and got a lot of atten...